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Creators/Authors contains: "Narayan, Akil"

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  1. ; ; (, Computer Methods in Applied Mechanics and Engineering)
    Free, publicly-accessible full text available May 1, 2026
  2. ; ; ; ; (, Proceedings of The International Conference on Machine Learning (ICML))
    Free, publicly-accessible full text available May 28, 2026
  3. ; ; ; ; (, SIAM/ASA Journal on Uncertainty Quantification)
    Free, publicly-accessible full text available December 31, 2025
  4. ; ; ; (, Computer Methods in Applied Mechanics and Engineering)
    Full Text Available 
  5. ; ; (, ESAIM: Mathematical Modelling and Numerical Analysis)
    The shallow water flow model is widely used to describe water flows in rivers, lakes, and coastal areas. Accounting for uncertainty in the corresponding transport-dominated nonlinear PDE models presents theoretical and numerical challenges that motivate the central advances of this paper. Starting with a spatially one-dimensional hyperbolicity-preserving, positivity-preserving stochastic Galerkin formulation of the parametric/uncertain shallow water equations, we derive an entropy-entropy flux pair for the system. We exploit this entropy-entropy flux pair to construct structure-preserving second-order energy conservative, and first- and second-order energy stable finite volume schemes for the stochastic Galerkin shallow water system. The performance of the methods is illustrated on several numerical experiments. 
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  6. ; ; ; ; ; (, SIAM/ASA Journal on Uncertainty Quantification)
    Full Text Available 
  7. ; ; ; ; ; (, Proceedings of The 27th International Conference on Artificial Intelligence and Statistics)
    Accepted Manuscript Full Text Available
  8. ; ; ; ; ; (, Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS))
  9. ; ; ; ; ; (, Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS))
    Accepted Manuscript Full Text Available
  10. ; ; (, Journal of Computational Physics)
    Full Text Available